Purpose: Align data efforts with business goals.
What We Do:

Build a prioritized roadmap of use cases with measurable ROI.

Define clear business outcomes for each initiative.

Ensure your Databricks platform design follows business needs, not just technology trends.

Offer strategic advisory services to evaluate current capabilities (people, processes, systems) and identify areas to capture data value.

Purpose: Deliver a future-ready data platform on the cloud.
What We Do:

Design and deploy Databricks environments across AWS, Azure, and Google Cloud.

Begin from your business use cases, not limitations of current architecture.

Provide cloud engineering & DevOps expertise to ensure enterprise-grade setup—secure, resilient, and high-performing.

Purpose: Turn ideas and problems into real data solutions.
What We Do:

Translate business ideas or pain points into concrete use cases.

Implement solutions across data engineering, analytics, BI, data science, and ML.

Deliver outcomes while managing the technical complexities ourselves—so you stay focused on the business.

Purpose: Accelerate time-to-value with proven patterns.
What We Do:

Deploy Databricks Solution Accelerators tailored to your business.

Cover verticals such as financial services, healthcare, retail, consumer goods, and manufacturing.

Quickly validate high-impact scenarios—like evaluating Generative AI for your use case.

Purpose: Maximize the value of your existing Databricks investment.
What We Do:

Review and assess current Databricks usage and performance.

Recommend improvements based on core requirements and business priorities.

Implement changes to reduce cost, boost performance, and enhance security.

Purpose: Go beyond experimentation and operationalize ML.
What We Do:

Integrate Databricks Machine Learning into your platform with production-grade workflows.

Establish robust MLOps practices to scale and govern models effectively.

Focus on delivering real business value, not just ML potential.